Exploring Complex Ornamental Genomes: The Rose as a Model Plant

Despite its high economic importance, little is known about rose genetics, genome structure, and the function of rose genes. Reasons for this lack of information are polyploidy in most cultivars, simple breeding strategies, high turnover rates for cultivars, and little public funding. Molecular and biotechnological tools developed during the genomics era now provide the means to fill this gap. This will be facilitated by a number of model traits as e.g., a small genome, a large genetic diversity including diploid genotypes, a comparatively short generation time and protocols for genetic engineering. A deeper understanding of genetic processes and the structure of the rose genome will serve several purposes: Applications to the breeding process including marker-assisted selection and direct manipulation of relevant traits via genetic engineering will lead to improved cultivars with new combinations of characters. In basic research, unique characters, e.g., the biosynthesis and emission of particular secondary metabolites will provide new information not available in model species. Furthermore comparative genomics will link information about the rose genome to ongoing projects on other rosaceous crops and will add to our knowledge about genome evolution and speciation. This review is intended as a presentation and is the compilation of the current knowledge on rose genetics and genomics, including functional genomics and genetic engineering. Furthermore, it is intended to show ways how knowledge on rose genetics and genomics can be linked to other species in the Rosaceae in order to utilize this information across genera.     

An infinitesimal model for quantitative trait genomic value prediction

We developed a marker based infinitesimal model for quantitative trait analysis. In contrast to the classical infinitesimal model, we now have new information about the segregation of every individual locus of the entire genome. Under this new model, we propose that the genetic effect of an individual locus is a function of the genome location (a continuous quantity). The overall genetic value of an individual is the weighted integral of the genetic effect function along the genome. Numerical integration is performed to find the integral, which requires partitioning the entire genome into a finite number of bins. Each bin may contain many markers. The integral is approximated by the weighted sum of all the bin effects. We now turn the problem of marker analysis into bin analysis so that the model dimension has decreased from a virtual infinity to a finite number of bins. This new approach can efficiently handle virtually unlimited number of markers without marker selection. The marker based infinitesimal model requires high linkage disequilibrium of all markers within a bin. For populations with low or no linkage disequilibrium, we develop an adaptive infinitesimal model. Both the original and the adaptive models are tested using simulated data as well as beef cattle data. The simulated data analysis shows that there is always an optimal number of bins at which the predictability of the bin model is much greater than the original marker analysis. Result of the beef cattle data analysis indicates that the bin model can increase the predictability from 10% (multiple marker analysis) to 33% (multiple bin analysis). The marker based infinitesimal model paves a way towards the solution of genetic mapping and genomic selection using the whole genome sequence data.     

Informed Consent in Direct‐to‐Consumer Personal Genome Testing: The Outline of A Model between Specific and Generic Consent

Broad genome‐wide testing is increasingly finding its way to the public through the online direct‐to‐consumer marketing of so‐called personal genome tests. Personal genome tests estimate genetic susceptibilities to multiple diseases and other phenotypic traits simultaneously. Providers commonly make use of Terms of Service agreements rather than informed consent procedures. However, to protect consumers from the potential physical, psychological and social harms associated with personal genome testing and to promote autonomous decision‐making with regard to the testing offer, we argue that current practices of information provision are insufficient and that there is a place – and a need – for informed consent in personal genome testing, also when it is offered commercially. The increasing quantity, complexity and diversity of most testing offers, however, pose challenges for information provision and informed consent. Both specific and generic models for informed consent fail to meet its moral aims when applied to personal genome testing. Consumers should be enabled to know the limitations, risks and implications of personal genome testing and should be given control over the genetic information they do or do not wish to obtain. We present the outline of a new model for informed consent which can meet both the norm of providing sufficient information and the norm of providing understandable information. The model can be used for personal genome testing, but will also be applicable to other, future forms of broad genetic testing or screening in commercial and clinical settings.     

Complete genome sequence of Streptococcus pneumoniae strain ST556, a multidrug-resistant isolate from an otitis media patient

Streptococcus pneumoniae is a major pathogen causing bacterial infection in the middle ear of humans. We previously used S. pneumoniae strain ST556, a low-passage 19F isolate from an otitis media patient, to perform a whole-genome screen for ear infection-associated genes in a chinchilla model. This report presents the complete genome sequence of ST556. The genome sequence will provide information complementary to the experimental data from our genetic study of this strain.     

Bread matters: a national initiative to profile the genetic diversity of Australian wheat

The large and complex genome of wheat makes genetic and genomic analysis in this important species both expensive and resource intensive. The application of next-generation sequencing technologies is particularly resource intensive, with at least 17?Gbp of sequence data required to obtain minimal (1×) coverage of the genome. A similar volume of data would represent almost 40× coverage of the rice genome. Progress can be made through the establishment of consortia to produce shared genomic resources. Australian wheat genome researchers, working with Bioplatforms Australia, have collaborated in a national initiative to establish a genetic diversity dataset representing Australian wheat germplasm based on whole genome next-generation sequencing data. Here, we describe the establishment and validation of this resource which can provide a model for broader international initiatives for the analysis of large and complex genomes.     

Haplotype reconstruction from SNP fragments by minimum error correction

MOTIVATION: Haplotype reconstruction based on aligned single nucleotide polymorphism (SNP) fragments is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. An important computational model of this problem is the minimum error correction (MEC) model, which has been mentioned in several literatures. The model retrieves a pair of haplotypes by correcting minimum number of SNPs in given genome fragments coming from an individual's DNA. RESULTS: In the first part of this paper, an exact algorithm for the MEC model is presented. Owing to the NP-hardness of the MEC model, we also design a genetic algorithm (GA). The designed GA is intended to solve large size problems and has very good performance. The strength and weakness of the MEC model are shown using experimental results on real data and simulation data. In the second part of this paper, to improve the MEC model for haplotype reconstruction, a new computational model is proposed, which simultaneously employs genotype information of an individual in the process of SNP correction, and is called MEC with genotype information (shortly, MEC/GI). Computational results on extensive datasets show that the new model has much higher accuracy in haplotype reconstruction than the pure MEC model.     

Advances in the human genome project – A review

While celebrating its fifth official birthday last year it seems that the Human Genome Project (HGP) has and will continue to yield important biochemical information to mankind. It is exhilarating to think about the transition from studying genome structure to understanding genome function. The collective actions of information dessimination, technology development for efficient and faster sequencing, high-volume sequencing and developing model organisms has led to its success sofar. Various genome-wide STS-based human maps were completed in 1995, including a genetic map, a YAC map, a RH map with, and an integrated YAC-RH genetic map. These maps provide comprehensive frameworks for positioning additional loci, with the current genetic and RH maps spanning essentially 100% of the human genome and the YAC maps covering 95%. Few genes, however, have yet been localized on these framework maps. To date the Human Genome Project has experienced gratifying success. The technology and data produced by the genome project will provide a strong stimulus to broad areas of biological research and biotechnology. However, enormous challenges remain.     

The FlyBase database of the Drosophila genome projects and community literature

FlyBase (http://flybase.bio.indiana.edu/) provides an integrated view of the fundamental genomic and genetic data on the major genetic model Drosophila melanogaster and related species. FlyBase has primary responsibility for the continual reannotation of the D. melanogaster genome. The ultimate goal of the reannotation effort is to decorate the euchromatic sequence of the genome with as much biological information as is available from the community and from the major genome project centers. A complete revision of the annotations of the now-finished euchromatic genomic sequence has been completed. There are many points of entry to the genome within FlyBase, most notably through maps, gene products and ontologies, structured phenotypic and gene expression data, and anatomy.     

The chicken genome and the developmental biologist

Recently the initial draft sequence of the chicken genome was released. The reasons for sequencing the chicken were to boost research and applications in agriculture and medicine, through its use as a model of vertebrate development. In addition, the sequence of the chicken would provide an important anchor species in the phylogenetic study of genome evolution. The chicken genome project has its roots in a decade of map building by genetic and physical mapping methods. Chicken genetic markers for map building have generally depended on labour intensive screening procedures. In recent years this has all changed with the availability of over 450,000 EST sequences, a draft sequence of the entire chicken genome and a map of over 1 million SNPs. Clearly, the future for the chicken genome and developmental biology is an exciting one. Through the integration of these resources, it will be possible to solve challenging scientific questions exploiting the power of a chicken model. In this paper we review progress in chicken genomics and discuss how the new tools and information on the chicken genome can help the developmental biologists now and in the future.     

The prebiotic evolutionary advantage of transferring genetic information from RNA to DNA

In the early 'RNA world' stage of life, RNA stored genetic information and catalyzed chemical reactions. However, the RNA world eventually gave rise to the DNA-RNA-protein world, and this transition included the 'genetic takeover' of information storage by DNA. We investigated evolutionary advantages for using DNA as the genetic material. The error rate of replication imposes a fundamental limit on the amount of information that can be stored in the genome, as mutations degrade information. We compared misincorporation rates of RNA and DNA in experimental non-enzymatic polymerization and calculated the lowest possible error rates from a thermodynamic model. Both analyses found that RNA replication was intrinsically error-prone compared to DNA, suggesting that total genomic information could increase after the transition to DNA. Analysis of the transitional RNA/DNA hybrid duplexes showed that copying RNA into DNA had similar fidelity to RNA replication, so information could be maintained during the genetic takeover. However, copying DNA into RNA was very error-prone, suggesting that attempts to return to the RNA world would result in a considerable loss of information. Therefore, the genetic takeover may have been driven by a combination of increased chemical stability, increased genome size and irreversibility.     

The European Renal Genome Project

Rapid progress in genome research creates a wealth of information on the functional annotation of mammalian genome sequences. However, as we accumulate large amounts of scientific information we are facing problems of how to integrate and relate the data produced by various genomic approaches. Here, we propose a novel concept of an organ atlas where diverse data from expression maps to histological findings to mutant phenotypes can be queried, compared and visualized in the context of a three dimensional reconstruction of the organ. We will seek proof of concept for the organ atlas by elucidating genetic pathways involved in development and pathophysiology of the kidney. Such a kidney atlas may provide a paradigm for a new systems-biology approach in functional genome research aimed at understanding the genetic basis of organ development, physiology and disease.     

'Natural selection merely modified while redundancy created'--Susumu Ohno's idea of the evolutionary importance of gene and genome duplications

Susumo Ohno's influential book Evolution by gene duplication dealt with the idea that gene and genome duplication events are the principal forces by which the genetic raw material is provided for increasing complexity during evolution. In 1970, the evidence for this hypothesis consisted mostly of karyotypic information, crude information by today's standard genetic data, DNA sequences. Nonetheless, although the type of data are outdated, the idea remained current and is still debated today in the age of complete genome sequences. Even more than thirty years after the initial publication more research than ever is being carried out on the evolutionary significance of gene and genome duplications and the contribution of these mechanisms to the advances in genomic and organismal evolution.     

The European Renal Genome Project: An Integrated Approach Towards Understanding the Genetics of Kidney Development and Disease

Rapid progress in genome research creates a wealth of information on the functional annotation of mammalian genome sequences. However, as we accumulate large amounts of scientific information we are facing problems of how to integrate and relate the data produced by various genomic approaches. Here, we propose the novel concept of an organ atlas where diverse data from expression maps to histological findings to mutant phenotypes can be queried, compared and visualized in the context of a three-dimensional reconstruction of the organ. We will seek proof of concept for the organ atlas by elucidating genetic pathways involved in development and pathophysiology of the kidney. Such a kidney atlas may provide a paradigm for a new systems-biology approach in functional genome research aimed at understanding the genetic bases of organ development, physiology and disease.Key Words: EuReGene, kidney, genome, development, pathophysiology, genetics     

Avian genomics in the 21st century

The chicken has long been an important model organism for developmental biology, as well as a major source of protein with billions of birds used in meat and egg production each year. Chicken genomics has been transformed in recent years, with the characterisation of large EST collections and most recently with the assembly of the chicken genome sequence. As the first livestock genome to be fully sequenced it leads the way for others to follow--with zebra finch later this year. The genome sequence and the availability of three million genetic polymorphisms are expected to aid the identification of genes that control traits of importance in poultry. As the first bird genome to be sequenced it is a model for the remaining 9,600 species thought to exist today. Many of the features of avian biology and organisation of the chicken genome make it an ideal model organism for phylogenetics and embryology, along with applications in agriculture and medicine. The availability of new tools such as whole-genome gene expression arrays and SNP panels, coupled with information resources on the genes and proteins are likely to enhance this position.     

'Natural selection merely modified while redundancy created' – Susumu Ohno's idea of the evolutionary importance of gene and genome duplications

Susumo Ohno's influential book Evolution by gene duplication dealt with the idea that gene and genome duplication events are the principal forces by which the genetic raw material is provided for increasing complexity during evolution. In 1970, the evidence for this hypothesis consisted mostly of karyotypic information, crude information by today's standard genetic data, DNA sequences. Nonetheless, although the type of data are outdated, the idea remained current and is still debated today in the age of complete genome sequences. Even more than thirty years after the initial publication more research than ever is being carried out on the evolutionary significance of gene and genome duplications and the contribution of these mechanisms to the advances in genomic and organismal evolution.     

ETph: enhancers and their targets in pig and human database

Enhancers, as the genomic non-coding sequences, play a key role in the activation of gene expression. They have been widely identified in the human genome. Pig is an important biomedical model for human health. Few studies have been performed to explore the enhancers in the pig genome. The human enhancer information may be useful to identify enhancers in the pig genome. In addition, the genetic background of pig traits could be useful to annotate human enhancers and diseases. Thus, in order to further study enhancers and their potential roles in human and pig, we developed a public database, ETph (Enhancers and their Targets in pig and human). ETph integrates the information on human enhancers, pig putative enhancers, target genes, pig QTL terms, human diseases, GO terms and the KEGG pathway. A total of 25 182 enhancers were identified in the pig genome using the human homology sequence information. Among them, 6232 high-confidence enhancers were used to build the ETph. ETph provides a convenient platform to search, browse and download data. Moreover, a web-based analytical tool was designed to visualize networks and topology graphs among pig putative enhancers, target genes, pig QTL traits and human diseases. ETph might provide a useful tool for researchers to investigate the genetic background of pig traits and human diseases. ETph is freely accessible at http://klab.sjtu.edu.cn/enhancer/ .     

AGAPE (Automated Genome Analysis PipelinE) for Pan-Genome Analysis of Saccharomyces cerevisiae

The characterization and public release of genome sequences from thousands of organisms is expanding the scope for genetic variation studies. However, understanding the phenotypic consequences of genetic variation remains a challenge in eukaryotes due to the complexity of the genotype-phenotype map. One approach to this is the intensive study of model systems for which diverse sources of information can be accumulated and integrated. Saccharomyces cerevisiae is an extensively studied model organism, with well-known protein functions and thoroughly curated phenotype data. To develop and expand the available resources linking genomic variation with function in yeast, we aim to model the pan-genome of S. cerevisiae. To initiate the yeast pan-genome, we newly sequenced or re-sequenced the genomes of 25 strains that are commonly used in the yeast research community using advanced sequencing technology at high quality. We also developed a pipeline for automated pan-genome analysis, which integrates the steps of assembly, annotation, and variation calling. To assign strain-specific functional annotations, we identified genes that were not present in the reference genome. We classified these according to their presence or absence across strains and characterized each group of genes with known functional and phenotypic features. The functional roles of novel genes not found in the reference genome and associated with strains or groups of strains appear to be consistent with anticipated adaptations in specific lineages. As more S. cerevisiae strain genomes are released, our analysis can be used to collate genome data and relate it to lineage-specific patterns of genome evolution. Our new tool set will enhance our understanding of genomic and functional evolution in S. cerevisiae, and will be available to the yeast genetics and molecular biology community.     

Exploiting the functional and taxonomic structure of genomic data by probabilistic topic modeling

In this paper, we present a method that enable both homology-based approach and composition-based approach to further study the functional core (i.e., microbial core and gene core, correspondingly). In the proposed method, the identification of major functionality groups is achieved by generative topic modeling, which is able to extract useful information from unlabeled data. We first show that generative topic model can be used to model the taxon abundance information obtained by homology-based approach and study the microbial core. The model considers each sample as a “document,” which has a mixture of functional groups, while each functional group (also known as a “latent topic”) is a weight mixture of species. Therefore, estimating the generative topic model for taxon abundance data will uncover the distribution over latent functions (latent topic) in each sample. Second, we show that, generative topic model can also be used to study the genome-level composition of “N-mer” features (DNA subreads obtained by composition-based approaches). The model consider each genome as a mixture of latten genetic patterns (latent topics), while each functional pattern is a weighted mixture of the “N-mer” features, thus the existence of core genomes can be indicated by a set of common N-mer features. After studying the mutual information between latent topics and gene regions, we provide an explanation of the functional roles of uncovered latten genetic patterns. The experimental results demonstrate the effectiveness of proposed method.